At a Glance
- Tasks: Design and implement data models, build data platforms, and collaborate with clients.
- Company: Join Red Olive, a passionate data consultancy focused on unlocking data value.
- Benefits: Flexible work environment, collaborative culture, and opportunities for professional growth.
- Other info: Inclusive team culture that values diverse perspectives and continuous learning.
- Why this job: Make a real impact by transforming data into actionable insights for clients.
- Qualifications: 5-7 years in data engineering, strong SQL and Python skills, and client-facing experience.
The predicted salary is between 55000 - 70000 £ per year.
We are Red Olive, a data consultancy that is passionate about helping organisations unlock the real value of their data. Our values - deep understanding, adding value quickly, and behaving ethically - guide everything we do.
The role involves being part of a friendly, close-knit team that enjoys collaborating, sharing ideas, and meeting up in our new London office. We also bring the whole company together every quarter for a full-team company day to celebrate wins and look ahead. This role is ideal for someone who has worked in smaller teams or organisations, where flexibility, ownership, and a broad skill set are valued just as much as deep technical expertise.
You’ll play a key role in designing and delivering data solutions - from building robust data platforms and pipelines through to designing effective data models that help organisations make better decisions. You’ll work closely with clients to understand their challenges, translate business requirements into practical data solutions, and communicate those solutions in a clear, accessible way.
Key responsibilities:
- Designing and implementing effective data models, including conceptual, logical, and dimensional models, to support analytics and reporting needs
- Applying data modelling best practices, including Kimball dimensional modelling principles, to create maintainable and high-quality data solutions
- Working directly with clients to understand their needs and translate business requirements into effective technical solutions
- Explaining technical concepts in a clear, jargon‑free way to non-technical stakeholders
- Designing and building scalable, reliable data platforms and ETL/ELT pipelines
- Building and managing data ingestion from APIs, flat files, and databases (SQL/NoSQL)
- Applying best practices in data modelling, governance, security, and data quality
- Supporting and mentoring junior team members
- Contributing to a culture of collaboration, learning, and continuous improvement
Requirements:
- Experience as a Data Engineer or within a data consultancy environment (typically 5 – 7 years)
- Strong experience designing and implementing data models, including dimensional modelling approaches such as Kimball methodology
- Experience translating business requirements into structured data solutions and designing models that support analytics, reporting, and decision-making
- Experience with the BEAM Agile Data Warehouse Design methodology
- Strong skills in SQL and Python (ideally T‑SQL and Spark SQL)
- Experience with at least one major cloud platform (Azure preferred), and tools such as Databricks, Spark, Fabric or Snowflake
- A working understanding of the Medallion architecture methodology
- Experience working with data warehousing concepts, data structures, and modelling best practices
- Comfortable working in smaller teams where priorities can shift and ownership is shared
- A confident communicator who can make complex ideas simple and actionable
- Someone who enjoys working with clients and building trusted relationships
- A thoughtful approach to data, with an interest in ethics, governance, and long‑term value
Interview Process:
There will be two rounds of interviews and a task in the middle. We know that great candidates don’t always meet every requirement listed. If this role excites you but your experience doesn’t align perfectly, we’d still love to hear from you. We welcome people from all backgrounds and especially value those who bring diverse perspectives, experiences, and ways of thinking. We are an equal opportunity employer and are committed to providing a fair and inclusive recruitment process, making reasonable adjustments where needed.
Senior Data Engineer & Modeller Consultant in London employer: Red Olive
At Red Olive, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our employees to thrive. Located in a vibrant area, we offer competitive benefits, continuous professional development opportunities, and a commitment to ethical practices that resonate with our values. Join us to be part of a team that not only values your contributions but also supports your growth in the dynamic field of data consultancy.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer & Modeller Consultant in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Red Olive!
✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Red Olive.
✨Apply Directly through Our Website
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We think you need these skills to ace Senior Data Engineer & Modeller Consultant in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Red Olive, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Red Olive. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Red Olive
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Red Olive!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
